Web analytics has come a long way with the emergence of marketing automation. But analytics is an exercise in futility unless the data makes sense and is put to good use.
The challenge is to identify crucial information from all of the mass data available and apply it to increase engagement and move the customers through the buying cycle. Marketers also need to separate high quality leads from low quality or casual leads and give priority to the former.
A key challenge is the numerous technology platforms existing in silos. Different platforms may provide data in different formats and standards. The marketers need to apply common standards to ensure consistency of data. A comprehensive dashboard that integrates the data and highlights quality leads is critical.
Analyzing big data to harvest leads can be overwhelming. Automation is the solution, but before applying automation, the marketer needs to make sure that every single step in the lead generating process is incorporated in the automated solution and that the process is fully automated.
Lead scoring depends on explicit information or information that the prospect supplies or information gleaned from the prospects’ online behavior and actions. For implicit information, the best approach is to glean the information out of your marketing automation tool rather than approach the customer to fill out lengthy forms every time. For explicit information, the marketer needs to understand actions that drive desirable behavior from the company’s viewpoint, the demographics that matter, and other relevant factors. The marketer next needs to ensure that the analytic tools deployed, tracks such information.
These activities are beyond the scope of marketing alone. An active involvement of the sales and IT teams becomes imperative to make optimal use of analytic data to drive engagement and increase conversions. But all in all, using data effectively can drastically improve your marketing efforts.